Perhaps the most natural way to understand probability is as an epistemic phenomenon. A probability function is an attempt to quantify a degree of uncertainty -- a state of mind. But some probabilities appear to be objective features of the world. A well constructed die has a probability of one in six that it will land on any given side, for instance. Such objective probabilities, or chances, explain why events happen with typical frequencies, while they cannot be predicted with certainty on any given trial. Philosophical controversies primarily arise regarding: the relationship between chances and epistemic states (under what circumstances should our degree of confidence match the chance, and why?); and also regarding the relationship between chances and frequencies (if chances are not reducible to frequencies, how do they explain those frequencies?).

Key works

Popper 1959 puts forth the propensity interpretation of probability, which has been an influential way of understanding chances; Lewis 1980 focuses upon epistemic aspects of chance, and is the focus of much literature relating to Humeanism and chance; Loewer 2004 is a helpful paper further exploring Lewis's metaphysics of chance; Albert 2000 discusses the time asymmetry of chance and its relation to temporal symmetries in physics.

Introductions

Consult Handfield 2012 for an exclusive focus upon chance; Hájek 2008 is about broader topic of probability, but has much that is of relevance to chance; Eagle 2010 contains many classic papers.

W. Stegmüller sees the decisive difficulty of the Laplacean interpretation of Carnaps probability in the lack of the required equiprobable possibilities. It is argued that the required equiprobabilities in physics are given by statistical mechanics and can easily be transferred from physics to general statistical problems.

In my recent article on these pages I argued that members of the Austrian School of economics have adopted and defended a faulty definition of probability. I argued that the definition of probability necessarily depends upon the nature of the world in which we live. I claimed that if the nature of the world is such that every event and phenomenon which occurs has a cause of some sort, then probability must be defined subjectively; that is, “as a measure of (...) our uncertainty about the likelihood of occurrence of some event or phenomenon, based upon evidence that need not derive solely from past frequencies of ‘collectives’ or ‘classes.’” I further claimed that the nature of the world is indeed such that all events and phenomena have prior causes, and that this fact compels us to adopt a subjective definition of probability.David Howden has recently published what he claims is a refutation of my argument in his article “Single Trial Probability Applications: Can Subjectivity Evade Frequency Limitations” . Unfortunately, Mr. Howden appears to not have understood my argument, and his purported refutation of my subjective definition consequently amounts to nothing more than a concatenation of confused and fallacious ideas that are completely irrelevant to my argument. David Howden has thus failed in his attempt to vindicate Richard von Mises’s definition of probability. (shrink)

Both Ludwig von Mises and Richard von Mises claimed that numerical probability could not be legitimately applied to singular cases. This paper challenges this aspect of the von Mises brothers’ theory of probability. It is argued that their denial that numerical probability could be applied to singular cases was based solely upon Richard von Mises’ exceptionally restrictive definition of probability. This paper challenges Richard von Mises’ definition of probability by arguing that the definition of probability necessarily depends upon whether the (...) world is governed by time-invariant causal laws. It is argued that if the world is governed by time-invariant causal laws, a subjective definition of probability must be adopted. It is further argued that both the nature of human action and the relative frequency method for calculating numerical probabilities both presuppose that the world is indeed governed by time-invariant causal laws. It is finally argued that the subjective definition of probability undercuts the von Mises claim that numerical probability cannot legitimately be applied to singular, non-replicable cases. (shrink)

In two recent papers Barry Loewer (2001, 2004) has suggested to interpret probabilities in statistical mechanics as Humean chances in David Lewis’ (1994) sense. I first give a precise formulation of this proposal, then raise two fundamental objections, and finally conclude that these can be overcome only at the price of interpreting these probabilities epistemically.

The best-system account of scientific law proposes that laws and chances are to be defined in terms of systematic interpretation of all occurrences: L is a law and the chance of X is p just in case L and the chance p of X are consequences of the ideal axiom system for the totality of events. So, what seem to be further facts beyond the occurrences are just matters of the best way to interpret the totality of physical events. This (...) paper proposes treating mentalistic concepts in a similar fashion: humans have consciousness in virtue of the fact that their brains’ best selfmonitoring, first-person interpretation of events involves consciousness. Apparent “further facts” about the mental realm are just matters of the brain’s native way to interpret itself. On this view, a philosopher’s “zombie” is just a normal human interpreted in a non-mentalistic way. (shrink)

This book sheds light on some recent discussions of the problems in probability theory and their history, analysing their philosophical and mathematical significance, and the role pf mathematical probability theory in other sciences.

Frequency probability theorists define an event’s probability distribution as the limit of a repeated set of trials belonging to a homogeneous collective. The subsets of this collective are events which we have deficient knowledge about on an individual level, although for the larger collective we have knowledge its aggregate behavior. Hence, probabilities can only be achieved through repeated trials of these subsets arriving at the established frequencies that define the probabilities. Crovelli argues that this is a mistaken approach, and that (...) a subjective assessment of individual trials should be used instead. Bifurcating between the two concepts of risk and uncertainty, Crovelli first asserts that probability is the tool used to manage uncertain situations, and then attempts to rebuild a definition of probability theory with this in mind. We show that such an attempt has little to gain, and results in an indeterminate application of entrepreneurial forecasting to uncertain decisions—a process far-removed from any application of probability theory. (shrink)